• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4814-4834
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• 2018

This paper presents an architecture for wireless sensor networks (WSNs) with blind source separation (BSS) applied to retrieve the received mixing signals of the sink nodes first. The little-to-no need of prior knowledge about the source signals of the sink nodes in the BSS method is obviously advantageous for WSNs. The optimization problem of the BSS of multiple independent source signals with complex and noncircular distributions from observed sensor nodes is considered and addressed. This paper applies Castella's reference-based scheme to Novey's negentropy-based algorithms, and then proposes a novel fast fixed-point (FastICA) algorithm, defined as the reference-signal negentropy complex FastICA (RSNT-cFastICA) for complex-valued noncircular-distribution source signals. The proposed method for the sink nodes is substantially more efficient than Novey's quasi-Newton algorithm in terms of computational speed under large numbers of samples, can effectively improve the power consumption effeciency of the sink nodes, and is significantly beneficial for WSNs and wireless communication networks (WCNs). The effectiveness and performance of the proposed method are validated and compared with three related BSS algorithms through theoretical analysis and simulations.

• Korean Journal of Optics and Photonics
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• v.28 no.6
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• pp.290-294
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• 2017

The Cassegrain telescope consists of a primary concave mirror and a secondary convex mirror. In the case of a secondary mirror, it is more difficult to test wavefront error than for a primary mirror, because it reflects the entire testing beam, as it is convex in shape. In this paper we tested the wavefront error of a complex aspheric convex secondary mirror by using the Simpson-Oland-Meckel Hindle test. To separate the systematic errors, such as fabrication error and alignment error of a meniscus lens, we adopted the QN absolute test (pixel-based absolute test using the quasi-Newton method) as well. Finally, we compared the measured result with that of an ASI (Aspheric Stitching Interferometer) made by the QED company, which resulted in an rms difference of only 2.5 nm, showing a similar shape of astigmatism aberration.

• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.1
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• pp.106-115
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• 1988

A numerical procedure for determining the airfoil shape that maximizes the lift is presented. The structure of the flow field is calculated by iteratively coupling potential flow and boundary analysis using the viscous-inviscid interaction method. The potential flow field is obtained by the vortex panel method and boundary layer flow is analyzed by means of integral approximation method which is capable of handling the laminar, transition and turbulent flow regimes. As the result of this study, it is found that the calculated flow regimes have good agreement with the existing experimented data. Davidon-Fletcher-Powell method and Augmented Lagrange Multiplier method are used for the optimal techniques. NACA 23012, NACA 65-3-21, NACA 64-2-415, NACA 64-2-A215 airfoils are used for determining the optimal airfoil shapes as a basic and compensate airfoils. Optimal design showed that the lift coefficients are increased by 17.4% at M$_{0}$=0.2 and 29% at M$_{0}$=0.3, compared with those of basic airfoil.oil.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.129-138
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• 2003

A new methodology for selecting spatially variable model control parameter values through consideration of inference models within a Hydroinformatic system has been developed to overcome problems associated with determination of spatially variable control parameter values for both ungauged and gauged catchment. The adopted Hydroinformatic tools for determination of control parameter values were a GIS(Arc/Info) to handle spatial and non-spatial attribute information, the SWMM(stormwater management model) to simulate catchment response to hydrologic events, and lastly, L_BFGS_B(a limited memory quasi-Newton algorithm) to assist in the calibration process. As a result, high accuracy of control parameter estimation was obtained by considering the spatial variations of the control parameters based on landuse characteristics. Also, considerable time and effort necessary for estimating a large number of control parameters were reduced from the new calibration approach.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.5
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• pp.661-669
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• 2007

Eyer since the Prandtl's experiment in 1934 and X-21 airjet test in 1950 both attempting to reduce drag, it was found that controlling the velocities of surface for extremely fast-moving object in the air through suction or injection was highly effective and active method. To obtain the right amount of suction or injection, however, repetitive trial-and error parameter test has been still used up to now. This study started from an attempt to decide optimal amount of suction and injection of incompressible Navier-Stokes by employing optimization techniques. However, optimization with traditional methods are very limited, especially when Reynolds number gets high and many unexpected variables emerges. In earlier study, we have proposed an algorithm to solve this problem by using step by step method in analysis and introducing SQP method in optimization. In this study, we propose more effective and robust algorithm and techniques in solving flow optimization problem.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.539-553
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• 2017

We propose a multi-state model to analyze semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the three states of the illness-death model: healthy, disease, and dead. The 'diseased' state can be considered as the intermediate event. Two more states are added into the illness-death model to incorporate the missing events, which are caused by a loss of follow-up before the end of a study. One of them is a state of the lost-to-follow-up (LTF), and the other is an unobservable state that represents an intermediate event experienced after the occurrence of LTF. Given covariates, we employ the Lin and Ying additive hazards model with log-normal frailty and construct a conditional likelihood to estimate transition intensities between states in the multi-state model. A marginalization of the full likelihood is completed using adaptive importance sampling, and the optimal solution of the regression parameters is achieved through an iterative quasi-Newton algorithm. Simulation studies are performed to investigate the finite-sample performance of the proposed estimation method in terms of empirical coverage probability of true regression parameters. Our proposed method is also illustrated with a dataset adapted from Helmer et al. (2001).